Are historical stage records useful to decrease the uncertainty of flood frequency analysis ? A 200-year long case study

Lucas, Mathieu; Renard, Benjamin; Coz, Jérôme Le; Lang, Michel; Bard, Antoine; Pierrefeu, Gilles

doi:10.1016/j.jhydrol.2023.129840

Cited by 3 publications

(5 citation statements)

References 73 publications

(100 reference statements)

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“…Before the ADCP-age (e.g., introduced for large rivers in Sweden in 1995 and in the UK in 2002) high flows were much harder, or impossible, to gauge without cable ways or bridges from which to suspend current meters. Older water level data were typically recorded using one or a few daily manual readings (Hamilton & Moore, 2012;Lucas et al, 2023;Westerberg et al, 2011) or manually digitized from chart recorder papers sometimes only as a daily average value. Chart recorders frequently lead to poor data resolution (cmscale) and temporally varying biases in water level due to poorly fitted/digitized paper, wet paper with spreading ink, or mechanical clock drift (Meles et al, 2022).…”

Section: Station Characteristicsmentioning

confidence: 99%

Sharing perceptual models of uncertainty: On the use of soft information about discharge data

Westerberg,

Karlsen

2024

Hydrological Processes

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Many hydrologists face the situation of having little or no information about the uncertainty in the hydrometeorological data they are using (e.g., Addor et al., 2020). Data uncertainty is rarely communicated by monitoring agencies and data providers-and is often not available on request. This means that data users typically treat data as if they are error-free, whereas in reality there can be large uncertainties and errors (McMillan et al., 2012). A striking example is that 50% of 1523 site-months of discharge data were found to be unreliable in a recent evaluation of the National Ecological Observatory Network streamflow estimates

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Section: Station Characteristicsmentioning

confidence: 99%

Sharing perceptual models of uncertainty: On the use of soft information about discharge data

Westerberg,

Karlsen

2024

Hydrological Processes

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“…As this uncertainty 140 can reach 30% at Beaucaire during the XIXth century (see following section 3.1), it seems necessary to consider it. We use the propagation procedure accounting for both stage and rating curve uncertainties described by Lucas et al (2023), that leads to s = 500 realisations of AMAX discharges: ! -O # -/ ,.…”

Section: Model A: Binomial Model For Historical Floods and Propagatio...mentioning

confidence: 99%

“…There is no tributary between the previous and the current station. A set of 500 realisations of AMAX floods from 1816 to 2020 is available from Lucas et al (2023), accounting for several sources of hydrometric uncertainty. The estimated 95% discharge uncertainty varies from 30% (XIXth century) to 5% .…”

Section: Discharge Data Over Five Centuriesmentioning

confidence: 99%

“…The models are first tested with a 205-year long series of AMAX values for the outlet of the Rhône River at Beaucaire, France. Lucas et al (2023) produced a detailed analysis of the uncertainty of this flood discharge series. It has been artificially subsampled in order to mimic a historical context, considering AMAX values on a 50-year period (1970-2020) and a collection 425 of 10 "historical" floods during the 1816-1969 period.…”

Section: Conclusion 420mentioning

confidence: 99%

“…The aim is to correctly assess the uncertainties of flood quantiles, based on historical information. This FFA model and several variants are applied to a case study based on the Rhône River at Beaucaire, France, offering a very long systematic record (1816-2020, 205 years), with discharge uncertainties carefully determined by Lucas et al (2023), 75 and a collection of historical floods from 1500 to 1815 (Pichard and Roucaute, 2014). In a first step, the 205-year systematic record is artificially subsampled in order to mimic a typical mixed dataset containing about 50 years of systematic data and about 150 years of censored historical data.…”

Section: Introductionmentioning

confidence: 99%

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A more comprehensive uncertainty framework for historical flood frequency analysis: a 500-year long case study

Lucas,

Lang,

Renard

et al. 2024

Preprint

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Abstract. The value of historical data for flood frequency analysis has been acknowledged and studied for a long time. A specific statistical framework must be used to comply with the censored nature of historical data. Indeed, it is assumed that all floods having exceeded a given perception threshold were recorded as written testimonies or flood marks. Conversely, all years without a flood record in the historical period are assumed to have a maximum discharge below the perception threshold. This paper proposes a Binomial model which explicitly recognizes the uncertain nature of both the perception threshold and the starting date of the historical period. This model is applied to a case study for the Rhône River at Beaucaire, France, where a long (1816–2020) systematic series of annual maximum discharges is available along with a collection of 13 historical floods from documentary evidences over three centuries (1500–1815). Results indicate that the inclusion of historical floods reduces the uncertainty of 100- or 1000-year flood quantiles, even when only the number of perception threshold exceedances is known. However, ignoring the uncertainty around the perception threshold leads to a noticeable underestimation of flood quantiles uncertainty. A qualitatively similar conclusion is found when ignoring the uncertainty around the historical period length. However, its impact on flood quantiles uncertainty appears to be much smaller than that of the perception threshold.

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Reconstructing the 1968 River Chew flash flood: merging a HEC-RAS 2D hydraulic modelling approach with historical evidence

Sabeti,

Stamataki,

Kjeldsen

2024

Geomatics, Natural Hazards and Risk

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Are historical stage records useful to decrease the uncertainty of flood frequency analysis ? A 200-year long case study

Cited by 3 publications

References 73 publications

Sharing perceptual models of uncertainty: On the use of soft information about discharge data

Sharing perceptual models of uncertainty: On the use of soft information about discharge data

A more comprehensive uncertainty framework for historical flood frequency analysis: a 500-year long case study

Reconstructing the 1968 River Chew flash flood: merging a HEC-RAS 2D hydraulic modelling approach with historical evidence

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